This study retrospectively analyzes prospectively collected data.
Here we aim to develop predictive models for 3-month medical and surgical readmission after elective lumbar surgery, based on a multi-institutional, national spine registry.
Unplanned readmissions place considerable stress on payers, hospitals, and patients. Medicare data reveals a 30-day readmission rate of 7.8% for lumbar-decompressions and 13.0% for lumbar-fusions, and hospitals are now being penalized for excessive 30-day readmission rates by virtue of the Hospital Readmissions Reduction Program.
The Quality and Outcomes Database (QOD) was queried for patients undergoing elective lumbar surgery for degenerative diseases. The QOD prospectively captures 3-month readmissions through electronic medical record (EMR) review and self-reported outcome questionnaires. Distinct multivariable logistic regression models were fitted for surgery-related and medical readmissions adjusting for patient and surgery-specific variables.
Of the total 33,674 patients included in this study 2079 (6.15%) reported at least one readmission during the 90-day postoperative period. The odds of medical readmission were significantly higher for older patients, males versus females, African Americans versus Caucasion, those with higher American Society of Anesthesiologists (ASA) grade, diabetes, coronary artery disease, higher numbers of involved levels, anterior only or anterior–posterior versus posterior approach; also, for patients who were unemployed compared with employed patients and those with high baseline Oswestry Disability Index (ODI). The odds of surgery-related readmission were significantly greater for patients with a higher body mass index (BMI), a higher ASA grade, female versus male, and African Americans versus Caucasians; also, for patients with severe depression, more involved spinal levels, anterior-only surgical approaches and higher baseline ODI scores.
In this study we present internally validated predictive models for medical and surgical readmission after elective lumbar spine surgery. These findings set the stage for targeted interventions with a potential to reduce unnecessary readmissions, and also suggest that medical and surgical readmissions be treated as distinct clinical events.
Level of Evidence: 3
Unplanned hospital readmissions place considerable stress on payers, hospitals, and patients. Hospitals are being penalized for excessive 30-day readmissions by virtue of the Hospital Readmissions Reduction Program. We aim to develop predictive models for 3-month medical and surgical readmission after elective lumbar surgery, based on a multi-institutional, national spine registry.
∗Department of Neurological Surgery, Vanderbilt University School of Medicine, Nashville, Tennessee
†Department of Orthopaedic Surgery, Vanderbilt University School of Medicine, Nashville, Tennessee
‡Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, Tennessee
§Department of Neurosurgery, The Pennsylvania State University, Hershey, Pennsylvania
¶University of Tennessee Health Science Center in Memphis, Tennessee
||Department of Neurological Surgery, Mayo Clinic, Rochester, Minnesota
∗∗Carolina Neurosurgery & Spine Associates, Carolinas Healthcare System, Charlotte, North Carolina
††Department of Physical Medicine & Rehabilitation, Vanderbilt University Medical Center, Nashville, Tennessee.
Address correspondence and reprint requests to Kristin R. Archer, PhD, DPT, Orthopedic Surgery & Rehabilitation and Physical Medicine and Rehabilitation, Vanderbilt University Medical Center, Medical Center East, South Tower, Suite 4200, Nashville, TN 37232-8774; E-mail: email@example.com
Received 23 May, 2018
Revised 16 July, 2018
Accepted 22 August, 2018
The manuscript submitted does not contain information about medical device(s)/drug(s).
No funds were received in support of this work.
Relevant financial activities outside the submitted work: consultancy, grants, stocks, expert testimony.